3D structures of individual mammalian genomes studied by single-cell Hi-C

Stochastic motion and transcriptional dynamics of pairs of distal DNA loci on a compacted chromosome

Chromosomes in the eukaryotic nucleus are highly compacted. However, for many functional processes, including transcription initiation, the pairwise motion of distal chromosomal elements such as enhancers and promoters is essential and necessitates dynamic fluidity. Here, we used a live-imaging assay to simultaneously measure the positions of pairs of enhancers and promoters and their transcriptional output while systematically varying the genomic separation between these two DNA loci. Our analysis reveals the coexistence of a compact globular organization and fast subdiffusive dynamics. These combined features cause an anomalous scaling of polymer relaxation times with genomic separation leading to long-ranged correlations. Thus, encounter times of DNA loci are much less dependent on genomic distance than predicted by existing polymer models, with potential consequences for eukaryotic gene expression.

Recent advances in chromosome capture techniques unraveling 3D genome architecture in germ cells, health, and disease

In eukaryotes, the genome does not emerge in a specific shape but rather as a hierarchial bundle within the nucleus. This multifaceted genome organization consists of multiresolution cellular structures, such as chromosome territories, compartments, and topologically associating domains, which are frequently defined by architecture, design proteins including CTCF and cohesin, and chromatin loops. This review briefly discusses the advances in understanding the basic rules of control, chromatin folding, and functional areas in early embryogenesis. With the use of chromosome capture techniques, the latest advancements in technologies for visualizing chromatin interactions come close to revealing 3D genome formation frameworks with incredible detail throughout all genomic levels, including at single-cell resolution. The possibility of detecting variations in chromatin architecture might open up new opportunities for disease diagnosis and prevention, infertility treatments, therapeutic approaches, desired exploration, and many other application scenarios.

Histone exchange sensors reveal variant specific dynamics in mouse embryonic stem cells

Eviction of histones from nucleosomes and their exchange with newly synthesized or alternative variants is a central epigenetic determinant. Here, we define the genome-wide occupancy and exchange pattern of canonical and non-canonical histone variants in mouse embryonic stem cells by genetically encoded exchange sensors. While exchange of all measured variants scales with transcription, we describe variant-specific associations with transcription elongation and Polycomb binding. We found considerable exchange of H3.1 and H2B variants in heterochromatin and repeat elements, contrasting the occupancy and little exchange of H3.3 in these regions. This unexpected association between H3.3 occupancy and exchange of canonical variants is also evident in active promoters and enhancers, and further validated by reduced H3.1 dynamics following depletion of H3.3-specific chaperone, HIRA. Finally, analyzing transgenic mice harboring H3.1 or H3.3 sensors demonstrates the vast potential of this system for studying histone exchange and its impact on gene expression regulation in vivo.

RBBP4 is an epigenetic barrier for the induced transition of pluripotent stem cells into totipotent 2C-like cells

Cellular totipotency is critical for whole-organism generation, yet how totipotency is established remains poorly illustrated. Abundant transposable elements (TEs) are activated in totipotent cells, which is critical for embryonic totipotency. Here, we show that the histone chaperone RBBP4, but not its homolog RBBP7, is indispensable for maintaining the identity of mouse embryonic stem cells (mESCs). Auxin-induced degradation of RBBP4, but not RBBP7, reprograms mESCs to the totipotent 2C-like cells. Also, loss of RBBP4 enhances transition from mESCs to trophoblast cells. Mechanistically, RBBP4 binds to the endogenous retroviruses (ERVs) and functions as an upstream regulator by recruiting G9a to deposit H3K9me2 on ERVL elements, and recruiting KAP1 to deposit H3K9me3 on ERV1/ERVK elements, respectively. Moreover, RBBP4 facilitates the maintenance of nucleosome occupancy at the ERVK and ERVL sites within heterochromatin regions through the chromatin remodeler CHD4. RBBP4 depletion leads to the loss of the heterochromatin marks and activation of TEs and 2C genes. Together, our findings illustrate that RBBP4 is required for heterochromatin assembly and is a critical barrier for inducing cell fate transition from pluripotency to totipotency.

Enhancer Function in the 3D Genome

In this review, we consider various aspects of enhancer functioning in the context of the 3D genome. Particular attention is paid to the mechanisms of enhancer-promoter communication and the significance of the spatial juxtaposition of enhancers and promoters in 3D nuclear space. A model of an activator chromatin compartment is substantiated, which provides the possibility of transferring activating factors from an enhancer to a promoter without establishing direct contact between these elements. The mechanisms of selective activation of individual promoters or promoter classes by enhancers are also discussed.

Linking genome structures to functions by simultaneous single-cell Hi-C and RNA-seq

Much progress has been made recently in single-cell chromosome conformation capture technologies. However, a method that allows simultaneous profiling of chromatin architecture and gene expression has not been reported. Here, we developed an assay named "Hi-C and RNA-seq employed simultaneously" (HiRES) and performed it on thousands of single cells from developing mouse embryos. Single-cell three-dimensional genome structures, despite being heavily determined by the cell cycle and developmental stages, gradually diverged in a cell type-specific manner as development progressed. By comparing the pseudotemporal dynamics of chromatin interactions with gene expression, we found a widespread chromatin rewiring that occurred before transcription activation. Our results demonstrate that the establishment of specific chromatin interactions is tightly related to transcriptional control and cell functions during lineage specification.

scHi-CSim: a flexible simulator that generates high-fidelity single-cell Hi-C data for benchmarking

Single-cell Hi-C technology provides an unprecedented opportunity to reveal chromatin structure in individual cells. However, high sequencing cost impedes the generation of biological Hi-C data with high sequencing depths and multiple replicates for downstream analysis. Here, we developed a single-cell Hi-C simulator (scHi-CSim) that generates high-fidelity data for benchmarking. scHi-CSim merges neighboring cells to overcome the sparseness of data, samples interactions in distance-stratified chromosomes to maintain the heterogeneity of single cells, and estimates the empirical distribution of restriction fragments to generate simulated data. We demonstrated that scHi-CSim can generate high-fidelity data by comparing the performance of single-cell clustering and detection of chromosomal high-order structures with raw data. Furthermore, scHi-CSim is flexible to change sequencing depth and the number of simulated replicates. We showed that increasing sequencing depth could improve the accuracy of detecting topologically associating domains. We also used scHi-CSim to generate a series of simulated datasets with different sequencing depths to benchmark scHi-C clustering methods.

Mesoscale, long-time mixing of chromosomes and its connection to polymer dynamics

Chromosomes are arranged in distinct territories within the nucleus of animal cells. Recent experiments have shown that these territories overlap at their edges, suggesting partial mixing during interphase. Experiments that knock-down of condensin II proteins during interphase indicate increased chromosome mixing, which demonstrates control of the mixing. In this study, we use a generic polymer simulation to quantify the dynamics of chromosome mixing over time. We introduce the chromosome mixing index, which quantifies the mixing of distinct chromosomes in the nucleus. We find that the chromosome mixing index in a small confinement volume (as a model of the nucleus), increases as a power-law of the time, with the scaling exponent varying non-monotonically with self-interaction and volume fraction. By comparing the chromosome mixing index with both monomer subdiffusion due to (non-topological) intermingling of chromosomes as well as even slower reptation, we show that for relatively large volume fractions, the scaling exponent of the chromosome mixing index is related to Rouse dynamics for relatively weak chromosome attractions and to reptation for strong attractions. In addition, we extend our model to more realistically account for the situation of the Drosophila chromosome by including the heterogeneity of the polymers and their lengths to account for microphase separation of euchromatin and heterochromatin and their interactions with the nuclear lamina. We find that the interaction with the lamina further impedes chromosome mixing.

Long interspersed nuclear element 1 and B1/Alu repeats blueprint genome compartmentalization

The organization of the genome into euchromatin and heterochromatin has been known for almost 100 years [1]. More than 50% of mammalian genomes contain repetitive sequences [2,3]. Recently, a functional link between the genome and its folding has been identified [4,5]. Homotypic clustering of long interspersed nuclear element 1 (LINE1 or L1) and B1/Alu retrotransposons forms grossly exclusive nuclear domains that characterize and predict heterochromatin and euchromatin, respectively. The spatial segregation of L1 and B1/Alu-rich compartments is conserved in mammalian cells and can be rebuilt during the cell cycle and established de novo in early embryogenesis. Inhibition of L1 RNA drastically weakened homotypic repeat contacts and compartmental segregation, indicating that L1 plays a more significant role than just being a compartmental marker. This simple and inclusive genetic coding model of L1 and B1/Alu in shaping the macroscopic structure of the genome provides a plausible explanation for the remarkable conservation and robustness of its folding in mammalian cells. It also proposes a conserved core structure on which subsequent dynamic regulation takes place.

CscoreTool-M infers 3D sub-compartment probabilities within cell population

MOTIVATION

Computational inference of genome organization based on Hi-C sequencing has greatly aided the understanding of chromatin and nuclear organization in three dimensions (3D). However, existing computational methods fail to address the cell population heterogeneity. Here we describe a probabilistic-modeling-based method called CscoreTool-M that infers multiple 3D genome sub-compartments from Hi-C data.

RESULTS

The compartment scores inferred using CscoreTool-M represents the probability of a genomic region locating in a specific sub-compartment. Compared to published methods, CscoreTool-M is more accurate in inferring sub-compartments corresponding to both active and repressed chromatin. The compartment scores calculated by CscoreTool-M also help to quantify the levels of heterogeneity in sub-compartment localization within cell populations. By comparing proliferating cells and terminally differentiated non-proliferating cells, we show that the proliferating cells have higher genome organization heterogeneity, which is likely caused by cells at different cell-cycle stages. By analyzing 10 sub-compartments, we found a sub-compartment containing chromatin potentially related to the early-G1 chromatin regions proximal to the nuclear lamina in HCT116 cells, suggesting the method can deconvolve cell cycle stage-specific genome organization among asynchronously dividing cells. Finally, we show that CscoreTool-M can identify sub-compartments that contain genes enriched in housekeeping or cell-type-specific functions.

AVAILABILITY AND IMPLEMENTATION

https://github.com/scoutzxb/CscoreTool-M.

3D genome alterations and editing in pathology

The human genome is folded into a multi-level 3D structure that controls many nuclear functions including gene expression. Recently, alterations in 3D genome organization were associated with several genetic diseases and cancer. As a consequence, experimental approaches are now being developed to modify the global 3D genome organization and that of specific loci. Here, we discuss emerging experimental approaches of 3D genome editing that may prove useful in biomedicine.

Robust 3D modeling reveals spatiosyntenic properties of animal genomes

Animal genomes are organized into chromosomes that are remarkably conserved in their gene content, forming distinct evolutionary units (synteny). Using versatile chromosomal modeling, we infer three-dimensional topology of genomes from representative clades spanning the earliest animal diversification. We apply a partitioning approach using interaction spheres to compensate for varying quality of topological data. Using comparative genomics approaches, we test whether syntenic signal at gene pair, local, and whole chromosomal scale is reflected in the reconstructed spatial organization. We identify evolutionarily conserved three-dimensional networks at all syntenic scales revealing novel evolutionarily maintained interactors associated with known conserved local gene linkages (such as hox). We thus present evidence for evolutionary constraints that are associated with three-, rather than just two-, dimensional animal genome organization, which we term spatiosynteny. As more accurate topological data become available, together with validation approaches, spatiosynteny may become relevant in understanding the functionality behind the observed conservation of animal chromosomes.

Dissection of 3D chromosome organization in Streptomyces coelicolor A3(2) leads to biosynthetic gene cluster overexpression

The soil-dwelling filamentous bacteria, Streptomyces, is widely known for its ability to produce numerous bioactive natural products. Despite many efforts toward their overproduction and reconstitution, our limited understanding of the relationship between the host's chromosome three dimension (3D) structure and the yield of the natural products escaped notice. Here, we report the 3D chromosome organization and its dynamics of the model strain, Streptomyces coelicolor, during the different growth phases. The chromosome undergoes a dramatic global structural change from primary to secondary metabolism, while some biosynthetic gene clusters (BGCs) form special local structures when highly expressed. Strikingly, transcription levels of endogenous genes are found to be highly correlated to the local chromosomal interaction frequency as defined by the value of the frequently interacting regions (FIREs). Following the criterion, an exogenous single reporter gene and even complex BGC can achieve a higher expression after being integrated into the chosen loci, which may represent a unique strategy to activate or enhance the production of natural products based on the local chromosomal 3D organization.

3D genomics and its applications in precision medicine

Three-dimensional (3D) genomics is an emerging discipline that studies the three-dimensional structure of chromatin and the three-dimensional and functions of genomes. It mainly studies the three-dimensional conformation and functional regulation of intranuclear genomes, such as DNA replication, DNA recombination, genome folding, gene expression regulation, transcription factor regulation mechanism, and the maintenance of three-dimensional conformation of genomes. Self-chromosomal conformation capture (3C) technology has been developed, and 3D genomics and related fields have developed rapidly. In addition, chromatin interaction analysis techniques developed by 3C technologies, such as paired-end tag sequencing (ChIA-PET) and whole-genome chromosome conformation capture (Hi-C), enable scientists to further study the relationship between chromatin conformation and gene regulation in different species. Thus, the spatial conformation of plant, animal, and microbial genomes, transcriptional regulation mechanisms, interaction patterns of chromosomes, and the formation mechanism of spatiotemporal specificity of genomes are revealed. With the help of new experimental technologies, the identification of key genes and signal pathways related to life activities and diseases is sustaining the rapid development of life science, agriculture, and medicine. In this paper, the concept and development of 3D genomics and its application in agricultural science, life science, and medicine are introduced, which provides a theoretical basis for the study of biological life processes.

Gene silencing dynamics are modulated by transiently active regulatory elements

Transcriptional enhancers have been extensively characterized, but cis-regulatory elements involved in acute gene repression have received less attention. Transcription factor GATA1 promotes erythroid differentiation by activating and repressing distinct gene sets. Here, we study the mechanism by which GATA1 silences the proliferative gene Kit during murine erythroid cell maturation and define stages from initial loss of activation to heterochromatinization. We find that GATA1 inactivates a potent upstream enhancer but concomitantly creates a discrete intronic regulatory region marked by H3K27ac, short noncoding RNAs, and de novo chromatin looping. This enhancer-like element forms transiently and serves to delay Kit silencing. The element is ultimately erased via the FOG1/NuRD deacetylase complex, as revealed by the study of a disease-associated GATA1 variant. Hence, regulatory sites can be self-limiting by dynamic co-factor usage. Genome-wide analyses across cell types and species uncover transiently active elements at numerous genes during repression, suggesting that modulation of silencing kinetics is widespread.

A maximum-entropy model to predict 3D structural ensembles of chromatin from pairwise distances with applications to interphase chromosomes and structural variants

The principles that govern the organization of genomes, which are needed for an understanding of how chromosomes are packaged and function in eukaryotic cells, could be deciphered if the three-dimensional (3D) structures are known. Recently, single-cell imaging techniques have been developed to determine the 3D coordinates of genomic loci in vivo. Here, we introduce a computational method (Distance Matrix to Ensemble of Structures, DIMES), based on the maximum entropy principle, with experimental pairwise distances between loci as constraints, to generate a unique ensemble of 3D chromatin structures. Using the ensemble of structures, we quantitatively account for the distribution of pairwise distances, three-body co-localization, and higher-order interactions. The DIMES method can be applied to both small and chromosome-scale imaging data to quantify the extent of heterogeneity and fluctuations in the shapes across various length scales. We develop a perturbation method in conjunction with DIMES to predict the changes in 3D structures from structural variations. Our method also reveals quantitative differences between the 3D structures inferred from Hi-C and those measured in imaging experiments. Finally, the physical interpretation of the parameters extracted from DIMES provides insights into the origin of phase separation between euchromatin and heterochromatin domains.

Functional annotation of the animal genomes: An integrated annotation resource for the horse

The genomic sequence of the horse has been available since 2009, providing critical resources for discovering important genomic variants regarding both animal health and population structures. However, to fully understand the functional implications of these variants, detailed annotation of the horse genome is required. Due to the limited availability of functional data for the equine genome, as well as the technical limitations of short-read RNA-seq, existing annotation of the equine genome contains limited information about important aspects of gene regulation, such as alternate isoforms and regulatory elements, which are either not transcribed or transcribed at a very low level. To solve above problems, the Functional Annotation of the Animal Genomes (FAANG) project proposed a systemic approach to tissue collection, phenotyping, and data generation, adopting the blueprint laid out by the Encyclopedia of DNA Elements (ENCODE) project. Here we detail the first comprehensive overview of gene expression and regulation in the horse, presenting 39,625 novel transcripts, 84,613 candidate cis-regulatory elements (CRE) and their target genes, 332,115 open chromatin regions genome wide across a diverse set of tissues. We showed substantial concordance between chromatin accessibility, chromatin states in different genic features and gene expression. This comprehensive and expanded set of genomics resources will provide the equine research community ample opportunities for studies of complex traits in the horse.

Epigenetic Regulations in Mammalian Cells: Roles and Profiling Techniques

The genome is almost identical in all the cells of the body. However, the functions and morphologies of each cell are different, and the factors that determine them are the genes and proteins expressed in the cells. Over the past decades, studies on epigenetic information, such as DNA methylation, histone modifications, chromatin accessibility, and chromatin conformation have shown that these properties play a fundamental role in gene regulation. Furthermore, various diseases such as cancer have been found to be associated with epigenetic mechanisms. In this study, we summarized the biological properties of epigenetics and single-cell epigenomic profiling techniques, and discussed future challenges in the field of epigenetics.

Does multi-way, long-range chromatin contact data advance 3D genome reconstruction?

BACKGROUND

Methods for inferring the three-dimensional (3D) configuration of chromatin from conformation capture assays that provide strictly pairwise interactions, notably Hi-C, utilize the attendant contact matrix as input. More recent assays, in particular split-pool recognition of interactions by tag extension (SPRITE), capture multi-way interactions instead of solely pairwise contacts. These assays yield contacts that straddle appreciably greater genomic distances than Hi-C, in addition to instances of exceptionally high-order chromatin interaction. Such attributes are anticipated to be consequential with respect to 3D genome reconstruction, a task yet to be undertaken with multi-way contact data. However, performing such 3D reconstruction using distance-based reconstruction techniques requires framing multi-way contacts as (pairwise) distances. Comparing approaches for so doing, and assessing the resultant impact of long-range and multi-way contacts, are the objectives of this study.

RESULTS

We obtained 3D reconstructions via multi-dimensional scaling under a variety of weighting schemes for mapping SPRITE multi-way contacts to pairwise distances. Resultant configurations were compared following Procrustes alignment and relationships were assessed between associated Procrustes root mean square errors and key features such as the extent of multi-way and/or long-range contacts. We found that these features had surprisingly limited influence on 3D reconstruction, a finding we attribute to their influence being diminished by the preponderance of pairwise contacts.

CONCLUSION

Distance-based 3D genome reconstruction using SPRITE multi-way contact data is not appreciably affected by the weighting scheme used to convert multi-way interactions to pairwise distances.

Unveiling the Machinery behind Chromosome Folding by Polymer Physics Modeling

Understanding the mechanisms underlying the complex 3D architecture of mammalian genomes poses, at a more fundamental level, the problem of how two or multiple genomic sites can establish physical contacts in the nucleus of the cells. Beyond stochastic and fleeting encounters related to the polymeric nature of chromatin, experiments have revealed specific, privileged patterns of interactions that suggest the existence of basic organizing principles of folding. In this review, we focus on two major and recently proposed physical processes of chromatin organization: loop-extrusion and polymer phase-separation, both supported by increasing experimental evidence. We discuss their implementation into polymer physics models, which we test against available single-cell super-resolution imaging data, showing that both mechanisms can cooperate to shape chromatin structure at the single-molecule level. Next, by exploiting the comprehension of the underlying molecular mechanisms, we illustrate how such polymer models can be used as powerful tools to make predictions in silico that can complement experiments in understanding genome folding. To this aim, we focus on recent key applications, such as the prediction of chromatin structure rearrangements upon disease-associated mutations and the identification of the putative chromatin organizing factors that orchestrate the specificity of DNA regulatory contacts genome-wide.

A GC-centered view of 3D genome organization

In the past two decades, our understanding of how the genome of mammalian cells is spatially organized in the three-dimensional (3D) space of the nucleus and how key nuclear processes are orchestrated in this space has drastically expanded. While genome organization has been extensively studied at the nanoscale, the higher-order arrangement of individual portions of the genome with respect to their intranuclear as well as reciprocal placement is less thoroughly characterized. Emerging evidence points to the existence of a complex radial arrangement of chromatin in the nucleus. However, what shapes this radial organization and whether it has any functional implications remain elusive. In this mini review, we first summarize our current knowledge on this rather overlooked aspect of mammalian genome organization. We then present a theoretical framework for explaining how the genome might be radially organized, focusing on the role of the guanine and cytosine density along the linear genome. Last, we discuss outstanding questions, hoping to inspire future experiments and spark interest in this topic within the 3D genome community.

Joint tensor modeling of single cell 3D genome and epigenetic data with Muscle

Emerging single cell technologies that simultaneously capture long-range interactions of genomic loci together with their DNA methylation levels are advancing our understanding of three-dimensional genome structure and its interplay with the epigenome at the single cell level. While methods to analyze data from single cell high throughput chromatin conformation capture (scHi-C) experiments are maturing, methods that can jointly analyze multiple single cell modalities with scHi-C data are lacking. Here, we introduce Muscle, a semi-nonnegative joint decomposition of Multiple single cell tensors, to jointly analyze 3D conformation and DNA methylation data at the single cell level. Muscle takes advantage of the inherent tensor structure of the scHi-C data, and integrates this modality with DNA methylation. We developed an alternating least squares algorithm for estimating Muscle parameters and established its optimality properties. Parameters estimated by Muscle directly align with the key components of the downstream analysis of scHi-C data in a cell type specific manner. Evaluations with data-driven experiments and simulations demonstrate the advantages of the joint modeling framework of Muscle over single modality modeling or a baseline multi modality modeling for cell type delineation and elucidating associations between modalities. Muscle is publicly available at https://github.com/keleslab/muscle.

Chromosome territory reorganization through artificial chromosome fusion is compatible with cell fate determination and mouse development

Chromosomes occupy discrete spaces in the interphase cell nucleus, called chromosome territory. The structural and functional relevance of chromosome territory remains elusive. We fused chromosome 15 and 17 in mouse haploid embryonic stem cells (haESCs), resulting in distinct changes of territories in the cognate chromosomes, but with little effect on gene expression, pluripotency and gamete functions of haESCs. The karyotype-engineered haESCs were successfully implemented in generating heterozygous (2n = 39) and homozygous (2n = 38) mouse models. Mice containing the fusion chromosome are fertile, and their representative tissues and organs display no phenotypic abnormalities, suggesting unscathed development. These results indicate that the mammalian chromosome architectures are highly resilient, and reorganization of chromosome territories can be readily tolerated during cell differentiation and mouse development.

Deep generative modeling and clustering of single cell Hi-C data

Deciphering 3D genome conformation is important for understanding gene regulation and cellular function at a spatial level. The recent advances of single cell Hi-C technologies have enabled the profiling of the 3D architecture of DNA within individual cell, which allows us to study the cell-to-cell variability of 3D chromatin organization. Computational approaches are in urgent need to comprehensively analyze the sparse and heterogeneous single cell Hi-C data. Here, we proposed scDEC-Hi-C, a new framework for single cell Hi-C analysis with deep generative neural networks. scDEC-Hi-C outperforms existing methods in terms of single cell Hi-C data clustering and imputation. Moreover, the generative power of scDEC-Hi-C could help unveil the differences of chromatin architecture across cell types. We expect that scDEC-Hi-C could shed light on deepening our understanding of the complex mechanism underlying the formation of chromatin contacts.

Influence of ionic conditions on knotting in a coarse-grained model for DNA

We investigate knotting probabilities of long double-stranded DNA strands in a coarse-grained Kratky-Porod model for DNA with Monte Carlo simulations. Various ionic conditions are implemented by adjusting the effective diameter of monomers. We find that the occurrence of knots in DNA can be reinforced considerably by high salt conditions and confinement between plates. Likewise, knots can almost be dissolved completely in a low salt scenario. Comparisons with recent experiments confirm that the coarse-grained model is able to capture and quantitatively predict topological features of DNA and can be used for guiding future experiments on DNA knots.

Physics-Based Polymer Models to Probe Chromosome Structure in Single Molecules

Human chromosomes have a complex 3D spatial organization in the cell nucleus, which comprises a hierarchy of physical interactions across genomic scales. Such an architecture serves important functional roles, as genes and their regulators have to physically interact to control gene regulation. However, the molecular mechanisms underlying the formation of those contacts remain poorly understood. Here, we describe a polymer-physics-based approach to investigate the machinery shaping genome folding and function. In silico model predictions on DNA single-molecule 3D structures are validated against independent super-resolution single-cell microscopy data, supporting a scenario whereby chromosome architecture is controlled by thermodynamics mechanisms of phase separation. Finally, as an application of our methods, the validated single-polymer conformations of the theory are used to benchmark powerful technologies to probe genome structure, such as Hi-C, SPRITE, and GAM.

Chromatin Structure from Development to Ageing

Nuclear structure influences genome architecture, which contributes to determine patterns of gene expression. Global changes in chromatin dynamics are essential during development and differentiation, and are one of the hallmarks of ageing. This chapter describes the molecular dynamics of chromatin structure that occur during development and ageing. In the first part, we introduce general information about the nuclear lamina, the chromatin structure, and the 3D organization of the genome. Next, we detail the molecular hallmarks found during development and ageing, including the role of DNA and histone modifications, 3D genome dynamics, and changes in the nuclear lamina. Within the chapter we discuss the implications that genome structure has on the mechanisms that drive development and ageing, and the physiological consequences when these mechanisms fail.

Bibliometric analysis of single-cell sequencing researches on immune cells and their application of DNA damage repair in cancer immunotherapy

INTRODUCTION

In recent decades, single-cell sequencing technology has developed rapidly and used widely in various fields of life sciences, especially for the detection of immune cells. A bibliometric analysis of single-cell sequencing research work on immune cells published during the 2011-2021 period should provide new insight on the use of single-cell sequencing.

METHODS

We screened 1,460 publications on single-cell sequencing on immune cells according to the publication date, article type, language, and country.

REULTS

The United States published the first and largest number of articles, while China's research started relatively late, but ranked second in the number of publications. T cells were the most commonly studied immune cells by single-cell sequencing, followed by mononuclear macrophages. Cancer biology was the most common field of immune cell research by single-cell sequencing. Single-cell sequencing studies using γδ T cells were mainly in the fields of cancer biology and cell development, and focused over time from cell surface receptor to cell function. Through in-depth analysis of the articles on single-cell sequencing of T cells in the oncology field, our analysis found that immunotherapy and tumor microenvironment were the most popular research directions in recent years.

DISCUSSION

The combination of DNA damage repair and immunotherapy seems to provide a new strategy for cancer therapy.

Characterizing cis-regulatory elements using single-cell epigenomics

Cell type-specific gene expression patterns and dynamics during development or in disease are controlled by cis-regulatory elements (CREs), such as promoters and enhancers. Distinct classes of CREs can be characterized by their epigenomic features, including DNA methylation, chromatin accessibility, combinations of histone modifications and conformation of local chromatin. Tremendous progress has been made in cataloguing CREs in the human genome using bulk transcriptomic and epigenomic methods. However, single-cell epigenomic and multi-omic technologies have the potential to provide deeper insight into cell type-specific gene regulatory programmes as well as into how they change during development, in response to environmental cues and through disease pathogenesis. Here, we highlight recent advances in single-cell epigenomic methods and analytical tools and discuss their readiness for human tissue profiling.

Folding Features and Dynamics of 3D Genome Architecture in Plant Fungal Pathogens

The folding and dynamics of three-dimensional (3D) genome organization are fundamental for eukaryotes executing genome functions but have been largely unexplored in nonmodel fungi. Using high-throughput sequencing coupled with chromosome conformation capture (Hi-C) data, we generated two chromosome-level assemblies for Puccinia striiformis f. sp. tritici, a fungus causing stripe rust disease on wheat, for studying 3D genome architectures of plant pathogenic fungi. The chromatin organization of the fungus followed a combination of the fractal globule model and the equilibrium globule model. Surprisingly, chromosome compartmentalization was not detected. Dynamics of 3D genome organization during two developmental stages of P. striiformis f. sp. tritici indicated that regulation of gene activities might be independent of the changes of genome organization. In addition, chromatin conformation conservation was found to be independent of genome sequence synteny conservation among different fungi. These results highlighted the distinct folding principles of fungal 3D genomes. Our findings should be an important step toward a holistic understanding of the principles and functions of genome architecture across different eukaryotic kingdoms. IMPORTANCE Previously, our understanding of 3D genome architecture has mainly come from model mammals, insects, and plants. However, the organization and regulatory functions of 3D genomes in fungi are largely unknown. In this study, we comprehensively investigated P. striiformis f. sp. tritici, a plant fungal pathogen, and revealed distinct features of the 3D genome, comparing it with the universal folding feature of 3D genomes in higher eukaryotic organisms. We further suggested that there might be distinct regulatory mechanisms of gene expression that are independent of chromatin organization changes during the developmental stages of this rust fungus. Moreover, we showed that the evolutionary pattern of 3D genomes in this fungus is also different from the cases in mammalian genomes. In addition, the genome assembly pipeline and the generated two chromosome-level genomes will be valuable resources. These results highlighted the unexplored distinct features of 3D genome organization in fungi. Therefore, our study provided complementary knowledge to holistically understand the organization and functions of 3D genomes across different eukaryotes.

The dynamics of three-dimensional chromatin organization and phase separation in cell fate transitions and diseases

Cell fate transition is a fascinating process involving complex dynamics of three-dimensional (3D) chromatin organization and phase separation, which play an essential role in cell fate decision by regulating gene expression. Phase separation is increasingly being considered a driving force of chromatin folding. In this review, we have summarized the dynamic features of 3D chromatin and phase separation during physiological and pathological cell fate transitions and systematically analyzed recent evidence of phase separation facilitating the chromatin structure. In addition, we discuss current advances in understanding how phase separation contributes to physical and functional enhancer-promoter contacts. We highlight the functional roles of 3D chromatin organization and phase separation in cell fate transitions, and more explorations are required to study the regulatory relationship between 3D chromatin organization and phase separation. 3D chromatin organization (shown by Hi-C contact map) and phase separation are highly dynamic and play functional roles during early embryonic development, cell differentiation, somatic reprogramming, cell transdifferentiation and pathogenetic process. Phase separation can regulate 3D chromatin organization directly, but whether 3D chromatin organization regulates phase separation remains unclear.

Quantification of extracellular proteins, protein complexes and mRNAs in single cells by proximity sequencing

We present proximity sequencing (Prox-seq) for simultaneous measurement of proteins, protein complexes and mRNAs in thousands of single cells. Prox-seq combines proximity ligation assay with single-cell sequencing to measure proteins and their complexes from all pairwise combinations of targeted proteins, providing quadratically scaled multiplexing. We validate Prox-seq and analyze a mixture of T cells and B cells to show that it accurately identifies these cell types and detects well-known protein complexes. Next, by studying human peripheral blood mononuclear cells, we discover that naïve CD8+ T cells display the protein complex CD8-CD9. Finally, we study protein interactions during Toll-like receptor (TLR) signaling in human macrophages. We observe the formation of signal-specific protein complexes, find CD36 co-receptor activity and additive signal integration under lipopolysaccharide (TLR4) and Pam2CSK4 (TLR2) stimulation, and show that quantification of protein complexes identifies signaling inputs received by macrophages. Prox-seq provides access to an untapped measurement modality for single-cell phenotyping and can discover uncharacterized protein interactions in different cell types.

Micro-Topographies Induce Epigenetic Reprogramming and Quiescence in Human Mesenchymal Stem Cells

Biomaterials can control cell and nuclear morphology. Since the shape of the nucleus influences chromatin architecture, gene expression and cell identity, surface topography can control cell phenotype. This study provides fundamental insights into how surface topography influences nuclear morphology, histone modifications, and expression of histone-associated proteins through advanced histone mass spectrometry and microarray analysis. The authors find that nuclear confinement is associated with a loss of histone acetylation and nucleoli abundance, while pathway analysis reveals a substantial reduction in gene expression associated with chromosome organization. In light of previous observations where the authors found a decrease in proliferation and metabolism induced by micro-topographies, they connect these findings with a quiescent phenotype in mesenchymal stem cells, as further shown by a reduction of ribosomal proteins and the maintenance of multipotency on micro-topographies after long-term culture conditions. Also, this influence of micro-topographies on nuclear morphology and proliferation is reversible, as shown by a return of proliferation when re-cultured on a flat surface. The findings provide novel insights into how biophysical signaling influences the epigenetic landscape and subsequent cellular phenotype.

Multilevel view on chromatin architecture alterations in cancer

Chromosomes inside the nucleus are not located in the form of linear molecules. Instead, there is a complex multilevel genome folding that includes nucleosomes packaging, formation of chromatin loops, domains, compartments, and finally, chromosomal territories. Proper spatial organization play an essential role for the correct functioning of the genome, and is therefore dynamically changed during development or disease. Here we discuss how the organization of the cancer cell genome differs from the healthy genome at various levels. A better understanding of how malignization affects genome organization and long-range gene regulation will help to reveal the molecular mechanisms underlying cancer development and evolution.

Normalization and de-noising of single-cell Hi-C data with BandNorm and scVI-3D

Single-cell high-throughput chromatin conformation capture methodologies (scHi-C) enable profiling of long-range genomic interactions. However, data from these technologies are prone to technical noise and biases that hinder downstream analysis. We develop a normalization approach, BandNorm, and a deep generative modeling framework, scVI-3D, to account for scHi-C specific biases. In benchmarking experiments, BandNorm yields leading performances in a time and memory efficient manner for cell-type separation, identification of interacting loci, and recovery of cell-type relationships, while scVI-3D exhibits advantages for rare cell types and under high sparsity scenarios. Application of BandNorm coupled with gene-associating domain analysis reveals scRNA-seq validated sub-cell type identification.

Biomolecular Topology: Modelling and Analysis

With the great advancement of experimental tools, a tremendous amount of biomolecular data has been generated and accumulated in various databases. The high dimensionality, structural complexity, the nonlinearity, and entanglements of biomolecular data, ranging from DNA knots, RNA secondary structures, protein folding configurations, chromosomes, DNA origami, molecular assembly, to others at the macromolecular level, pose a severe challenge in their analysis and characterization. In the past few decades, mathematical concepts, models, algorithms, and tools from algebraic topology, combinatorial topology, computational topology, and topological data analysis, have demonstrated great power and begun to play an essential role in tackling the biomolecular data challenge. In this work, we introduce biomolecular topology, which concerns the topological problems and models originated from the biomolecular systems. More specifically, the biomolecular topology encompasses topological structures, properties and relations that are emerged from biomolecular structures, dynamics, interactions, and functions. We discuss the various types of biomolecular topology from structures (of proteins, DNAs, and RNAs), protein folding, and protein assembly. A brief discussion of databanks (and databases), theoretical models, and computational algorithms, is presented. Further, we systematically review related topological models, including graphs, simplicial complexes, persistent homology, persistent Laplacians, de Rham-Hodge theory, Yau-Hausdorff distance, and the topology-based machine learning models.

Every gene everywhere all at once: High-precision measurement of 3D chromosome architecture with single-cell Hi-C

The three-dimensional (3D) structure of chromosomes influences essential biological processes such as gene expression, genome replication, and DNA damage repair and has been implicated in many developmental and degenerative diseases. In the past two centuries, two complementary genres of technology-microscopy, such as fluorescence in situ hybridization (FISH), and biochemistry, such as chromosome conformation capture (3C or Hi-C)-have revealed general principles of chromosome folding in the cell nucleus. However, the extraordinary complexity and cell-to-cell variability of the chromosome structure necessitate new tools with genome-wide coverage and single-cell precision. In the past decade, single-cell Hi-C emerges as a new approach that builds upon yet conceptually differs from bulk Hi-C assays. Instead of measuring population-averaged statistical properties of chromosome folding, single-cell Hi-C works as a proximity-based "biochemical microscope" that measures actual 3D structures of individual genomes, revealing features hidden in bulk Hi-C such as radial organization, multi-way interactions, and chromosome intermingling. Single-cell Hi-C has been used to study highly dynamic processes such as the cell cycle, cell-type-specific chromosome architecture ("structure types"), and structure-expression interplay, deepening our understanding of DNA organization and function.

Decoding the spatial chromatin organization and dynamic epigenetic landscapes of macrophage cells during differentiation and immune activation

Immunocytes dynamically reprogram their gene expression profiles during differentiation and immunoresponse. However, the underlying mechanism remains elusive. Here, we develop a single-cell Hi-C method and systematically delineate the 3D genome and dynamic epigenetic atlas of macrophages during these processes. We propose "degree of disorder" to measure genome organizational patterns inside topologically-associated domains, which is correlated with the chromatin epigenetic states, gene expression, and chromatin structure variability in individual cells. Furthermore, we identify that NF-κB initiates systematic chromatin conformation reorganization upon Mycobacterium tuberculosis infection. The integrated Hi-C, eQTL, and GWAS analysis depicts the atlas of the long-range target genes of mycobacterial disease susceptible loci. Among these, the SNP rs1873613 is located in the anchor of a dynamic chromatin loop with LRRK2, whose inhibitor AdoCbl could be an anti-tuberculosis drug candidate. Our study provides comprehensive resources for the 3D genome structure of immunocytes and sheds insights into the order of genome organization and the coordinated gene transcription during immunoresponse.

Comparison and critical assessment of single-cell Hi-C protocols

Advances in single-cell sequencing technologies make it possible to study the genome architecture in single cells. The rapid growth of the field has been fueled by the development of innovative single-cell Hi-C protocols. However, the protocols vary considerably in their efficiency, bias, scale and costs, and their relative advantages for different applications are unclear.

Here, we compare the two most commonly used single-cell Hi-C protocols. We use long-read sequencing to analyze molecular products of the Hi-C assay and show that whole-genome amplification step results in increased number of artifacts, larger coverage biases, and increased amount of noise compared to PCR-based amplification. Our comparison provides guidance for researchers studying chromatin architecture in individual cells.

D2 Plot, a Matrix of DNA Density and Distance to Periphery, Reveals Functional Genome Regions

The execution of biological activities inside space-limited cell nuclei requires sophisticated organization. Current studies on the 3D genome focus on chromatin interactions and local structures, e.g., topologically associating domains (TADs). In this study, two global physical properties: DNA density and distance to nuclear periphery (DisTP), are introduced and a 2D matrix, D² plot, is constructed for mapping genetic and epigenetic markers. Distinct patterns of functional markers on the D² plot, indicating its ability to compartmentalize functional genome regions, are observed. Furthermore, enrichments of transcription-related markers are concatenated into a cross-species transcriptional activation model, where the nucleus is divided into four areas: active, intermediate, repress and histone, and repress and repeat. Based on the trajectories of the genomic regions on D² plot, the constantly active and newly activated genes are successfully identified during olfactory sensory neuron maturation. The analysis reveals that the D² plot effectively categorizes functional regions and provides a universal and transcription-related measurement for the 3D genome.

Multiple parameters shape the 3D chromatin structure of single nuclei at the doc locus in Drosophila

The spatial organization of chromatin at the scale of topologically associating domains (TADs) and below displays large cell-to-cell variations. Up until now, how this heterogeneity in chromatin conformation is shaped by chromatin condensation, TAD insulation, and transcription has remained mostly elusive. Here, we used Hi-M, a multiplexed DNA-FISH imaging technique providing developmental timing and transcriptional status, to show that the emergence of TADs at the ensemble level partially segregates the conformational space explored by single nuclei during the early development of Drosophila embryos. Surprisingly, a substantial fraction of nuclei display strong insulation even before TADs emerge. Moreover, active transcription within a TAD leads to minor changes to the local inter- and intra-TAD chromatin conformation in single nuclei and only weakly affects insulation to the neighboring TAD. Overall, our results indicate that multiple parameters contribute to shaping the chromatin architecture of single nuclei at the TAD scale.

On the robustness of machine learning algorithms toward microfluidic distortions for cell classification via on-chip fluorescence microscopy

Single-cell imaging and sorting are critical technologies in biology and clinical applications. The power of these technologies is increased when combined with microfluidics, fluorescence markers, and machine learning. However, this quest faces several challenges. One of these is the effect of the sample flow velocity on the classification performances. Indeed, cell flow speed affects the quality of image acquisition by increasing motion blur and decreasing the number of acquired frames per sample. We investigate how these visual distortions impact the final classification task in a real-world use-case of cancer cell screening, using a microfluidic platform in combination with light sheet fluorescence microscopy. We demonstrate, by analyzing both simulated and experimental data, that it is possible to achieve high flow speed and high accuracy in single-cell classification. We prove that it is possible to overcome the 3D slice variability of the acquired 3D volumes, by relying on their 2D sum z-projection transformation, to reach an efficient real time classification with an accuracy of 99.4% using a convolutional neural network with transfer learning from simulated data. Beyond this specific use-case, we provide a web platform to generate a synthetic dataset and to investigate the effect of flow speed on cell classification for any biological samples and a large variety of fluorescence microscopes (https://www.creatis.insa-lyon.fr/site7/en/MicroVIP).

Polyploidy and Myc Proto-Oncogenes Promote Stress Adaptation via Epigenetic Plasticity and Gene Regulatory Network Rewiring

Polyploid cells demonstrate biological plasticity and stress adaptation in evolution; development; and pathologies, including cardiovascular diseases, neurodegeneration, and cancer. The nature of ploidy-related advantages is still not completely understood. Here, we summarize the literature on molecular mechanisms underlying ploidy-related adaptive features. Polyploidy can regulate gene expression via chromatin opening, reawakening ancient evolutionary programs of embryonality. Chromatin opening switches on genes with bivalent chromatin domains that promote adaptation via rapid induction in response to signals of stress or morphogenesis. Therefore, stress-associated polyploidy can activate Myc proto-oncogenes, which further promote chromatin opening. Moreover, Myc proto-oncogenes can trigger polyploidization de novo and accelerate genome accumulation in already polyploid cells. As a result of these cooperative effects, polyploidy can increase the ability of cells to search for adaptive states of cellular programs through gene regulatory network rewiring. This ability is manifested in epigenetic plasticity associated with traits of stemness, unicellularity, flexible energy metabolism, and a complex system of DNA damage protection, combining primitive error-prone unicellular repair pathways, advanced error-free multicellular repair pathways, and DNA damage-buffering ability. These three features can be considered important components of the increased adaptability of polyploid cells. The evidence presented here contribute to the understanding of the nature of stress resistance associated with ploidy and may be useful in the development of new methods for the prevention and treatment of cardiovascular and oncological diseases.

Single-cell diploid Hi-C reveals the role of spatial aggregations in complex rearrangements and KMT2A fusions in leukemia

BACKGROUND

Simple translocations and complex rearrangements are formed through illegitimate ligations of double-strand breaks of fusion partners and lead to generation of oncogenic fusion genes that affect cellular function. The contact first hypothesis states that fusion partners tend to colocalize prior to fusion in normal cells. Here we test this hypothesis at the single-cell level and explore the underlying mechanism.

RESULTS

By analyzing published single-cell diploid Hi-C datasets, we find partner genes fused in leukemia exhibit smaller spatial distances than those fused in solid tumor and control gene pairs. Intriguingly, multiple partners tend to colocalize with KMT2A in the same cell. 3D genome architecture has little association with lineage decision of KMT2A fusion types in leukemia. Besides simple translocations, complex rearrangement-related KMT2A fusion genes (CRGs) also show closer proximity and belong to a genome-wide mutual proximity network. We find CRGs are co-expressed, co-localized, and enriched in the targets of the transcriptional factor RUNX1, suggesting they may be involved in RUNX1-mediated transcription factories. Knockdown of RUNX1 leads to significantly fewer contacts among CRGs. We also find CRGs are enriched in active transcriptional regions and loop anchors, and exhibit high levels of TOP2-mediated DNA breakages. Inhibition of transcription leads to reduced DNA breakages of CRGs.

CONCLUSIONS

Our results demonstrate KMT2A partners and CRGs may form dynamic and multipartite spatial clusters in individual cells that may be involved in RUNX1-mediated transcription factories, wherein massive DNA damages and illegitimate ligations of genes may occur, leading to complex rearrangements and KMT2A fusions in leukemia.

Gene regulation on extrachromosomal DNA

Oncogene amplification on extrachromosomal DNA (ecDNA) is prevalent in human cancer and is associated with poor outcomes. Clonal, megabase-sized circular ecDNAs in cancer are distinct from nonclonal, small sub-kilobase-sized DNAs that may arise during normal tissue homeostasis. ecDNAs enable profound changes in gene regulation beyond copy-number gains. An emerging principle of ecDNA regulation is the formation of ecDNA hubs: micrometer-sized nuclear structures of numerous copies of ecDNAs tethered by proteins in spatial proximity. ecDNA hubs enable cooperative and intermolecular sharing of DNA regulatory elements for potent and combinatorial gene activation. The 3D context of ecDNA shapes its gene expression potential, selection for clonal heterogeneity among ecDNAs, distribution through cell division, and reintegration into chromosomes. Technologies for studying gene regulation and structure of ecDNA are starting to answer long-held questions on the distinct rules that govern cancer genes beyond chromosomes.

A simulation model of heterochromatin formation at submolecular detail

Heterochromatin is a physical state of the chromatin fiber that maintains gene repression during cell development. Although evidence exists on molecular mechanisms involved in heterochromatin formation, a detailed structural mechanism of heterochromatin formation needs a better understanding. We made use of a simple Monte Carlo simulation model with explicit representation of key molecular events to observe molecular self-organization leading to heterochromatin formation. Our simulations provide a structural interpretation of several important traits of the heterochromatinization process. In particular, this study provides a depiction of how small amounts of HP1 are able to induce a highly condensed chromatin state through HP1 dimerization and bridging of sequence-remote nucleosomes. It also elucidates structural roots of a yet poorly understood phenomenon of a nondeterministic nature of heterochromatin formation and subsequent gene repression. Experimental chromatin in vivo assay provides an unbiased estimate of time scale of repressive response to a heterochromatin-triggering event.

Loop-extrusion and polymer phase-separation can co-exist at the single-molecule level to shape chromatin folding

Loop-extrusion and phase-separation have been proposed as mechanisms that shape chromosome spatial organization. It is unclear, however, how they perform relative to each other in explaining chromatin architecture data and whether they compete or co-exist at the single-molecule level. Here, we compare models of polymer physics based on loop-extrusion and phase-separation, as well as models where both mechanisms act simultaneously in a single molecule, against multiplexed FISH data available in human loci in IMR90 and HCT116 cells. We find that the different models recapitulate bulk Hi-C and average multiplexed microscopy data. Single-molecule chromatin conformations are also well captured, especially by phase-separation based models that better reflect the experimentally reported segregation in globules of the considered genomic loci and their cell-to-cell structural variability. Such a variability is consistent with two main concurrent causes: single-cell epigenetic heterogeneity and an intrinsic thermodynamic conformational degeneracy of folding. Overall, the model combining loop-extrusion and polymer phase-separation provides a very good description of the data, particularly higher-order contacts, showing that the two mechanisms can co-exist in shaping chromatin architecture in single cells.

scGAD: single-cell gene associating domain scores for exploratory analysis of scHi-C data

SUMMARY

Quantitative tools are needed to leverage the unprecedented resolution of single-cell high-throughput chromatin conformation (scHi-C) data and integrate it with other single-cell data modalities. We present single-cell gene associating domain (scGAD) scores as a dimension reduction and exploratory analysis tool for scHi-C data. scGAD enables summarization at the gene unit while accounting for inherent gene-level genomic biases. Low-dimensional projections with scGAD capture clustering of cells based on their 3D structures. Significant chromatin interactions within and between cell types can be identified with scGAD. We further show that scGAD facilitates the integration of scHi-C data with other single-cell data modalities by enabling its projection onto reference low-dimensional embeddings. This multi-modal data integration provides an automated and refined cell-type annotation for scHi-C data.

AVAILABILITY AND IMPLEMENTATION

scGAD is part of the BandNorm R package at https://sshen82.github.io/BandNorm/articles/scGAD-tutorial.html.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Integrative genome modeling platform reveals essentiality of rare contact events in 3D genome organizations

A multitude of sequencing-based and microscopy technologies provide the means to unravel the relationship between the three-dimensional organization of genomes and key regulatory processes of genome function. Here, we develop a multimodal data integration approach to produce populations of single-cell genome structures that are highly predictive for nuclear locations of genes and nuclear bodies, local chromatin compaction and spatial segregation of functionally related chromatin. We demonstrate that multimodal data integration can compensate for systematic errors in some of the data and can greatly increase accuracy and coverage of genome structure models. We also show that alternative combinations of different orthogonal data sources can converge to models with similar predictive power. Moreover, our study reveals the key contributions of low-frequency (‘rare’) interchromosomal contacts to accurately predicting the global nuclear architecture, including the positioning of genes and chromosomes. Overall, our results highlight the benefits of multimodal data integration for genome structure analysis, available through the Integrative Genome Modeling software package.

The Integrative Genome Modeling platform is a tool for population-based three-dimensional genome structure modeling and analysis by integrating various experimental data sources.